LostTech.TensorFlow : API Documentation

Type ReduceLROnPlateau

Namespace tensorflow.keras.callbacks

Parent Callback

Interfaces IReduceLROnPlateau

Reduce learning rate when a metric has stopped improving.

Models often benefit from reducing the learning rate by a factor of 2-10 once learning stagnates. This callback monitors a quantity and if no improvement is seen for a 'patience' number of epochs, the learning rate is reduced.

Show Example
reduce_lr = ReduceLROnPlateau(monitor='val_loss', factor=0.2,
                                          patience=5, min_lr=0.001)
            model.fit(X_train, Y_train, callbacks=[reduce_lr]) 



Public instance methods

bool in_cooldown()

object in_cooldown_dyn()

Public static methods

ReduceLROnPlateau NewDyn(ImplicitContainer<T> monitor, ImplicitContainer<T> factor, ImplicitContainer<T> patience, ImplicitContainer<T> verbose, ImplicitContainer<T> mode, ImplicitContainer<T> min_delta, ImplicitContainer<T> cooldown, ImplicitContainer<T> min_lr, IDictionary<string, object> kwargs)

Initialize self. See help(type(self)) for accurate signature.

Public properties

int best get; set;

int cooldown get; set;

int cooldown_counter get; set;

double factor get; set;

double min_delta get; set;

int min_lr get; set;

string mode get; set;

object model get; set;

string monitor get; set;

object monitor_op get; set;

object params get; set;

int patience get; set;

object PythonObject get;

object validation_data get; set;

int verbose get; set;

int wait get; set;